Evidence map›Paper›PMID 26968660›Full record

ArticleBMC genomics2016

ChlamyNET: a Chlamydomonas gene co-expression network reveals global properties of the transcriptome and the early setup of key co-expression patterns in the green lineage.

Francisco J Romero-Campero, Ignacio Perez-Hurtado, Eva Lucas-Reina, Jose M Romero, Federico Valverde

Open access · goldAbstract read
In one paragraph

Article in BMC genomics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed
1.4field-weighted citation impact, top 19% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

21 citing papers in PubMed, 43 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 2 institutions in 1 country.

Francisco J Romero-CamperoDepartamento de Ciencias de la Computación e Inteligencia Artificial, Universidad de Sevilla, Reina Mercedes s/n, 41012, Sevilla, Spain.
Ignacio Perez-HurtadoDepartamento de Ciencias de la Computación e Inteligencia Artificial, Universidad de Sevilla, Reina Mercedes s/n, 41012, Sevilla, Spain.
Eva Lucas-ReinaInstituto de Bioquímica Vegetal y Fotosíntesis, Universidad de Sevilla-CSIC, Americo Vespucio 49, 41092, Sevilla, Spain.
Jose M RomeroInstituto de Bioquímica Vegetal y Fotosíntesis, Universidad de Sevilla-CSIC, Americo Vespucio 49, 41092, Sevilla, Spain.
Federico ValverdeInstituto de Bioquímica Vegetal y Fotosíntesis, Universidad de Sevilla-CSIC, Americo Vespucio 49, 41092, Sevilla, Spain. federico.valverde@ibvf.csic.es.ORCID http://orcid.org/0000-0001-8063-0974
Instituto de Bioquímica Vegetal y Fotosíntesis · ESUniversidad de Sevilla · ES

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundChlamydomonas reinhardtii is the model organism that serves as a reference for studies in algal genomics and physiology. It is of special interest in the study of the evolution of regulatory pathways from algae to higher plants. Additionally, it has recently gained attention as a potential source for bio-fuel and bio-hydrogen production. The genome of Chlamydomonas is available, facilitating the analysis of its transcriptome by RNA-seq data. This has produced a massive amount of data that remains fragmented making necessary the application of integrative approaches based on molecular systems biology.

resultsWe constructed a gene co-expression network based on RNA-seq data and developed a web-based tool, ChlamyNET, for the exploration of the Chlamydomonas transcriptome. ChlamyNET exhibits a scale-free and small world topology. Applying clustering techniques, we identified nine gene clusters that capture the structure of the transcriptome under the analyzed conditions. One of the most central clusters was shown to be involved in carbon/nitrogen metabolism and signalling, whereas one of the most peripheral clusters was involved in DNA replication and cell cycle regulation. The transcription factors and regulators in the Chlamydomonas genome have been identified in ChlamyNET. The biological processes potentially regulated by them as well as their putative transcription factor binding sites were determined. The putative light regulated transcription factors and regulators in the Chlamydomonas genome were analyzed in order to provide a case study on the use of ChlamyNET. Finally, we used an independent data set to cross-validate the predictive power of ChlamyNET.

conclusionsThe topological properties of ChlamyNET suggest that the Chlamydomonas transcriptome posseses important characteristics related to error tolerance, vulnerability and information propagation. The central part of ChlamyNET constitutes the core of the transcriptome where most authoritative hub genes are located interconnecting key biological processes such as light response with carbon and nitrogen metabolism. Our study reveals that key elements in the regulation of carbon and nitrogen metabolism, light response and cell cycle identified in higher plants were already established in Chlamydomonas. These conserved elements are not only limited to transcription factors, regulators and their targets, but also include the cis-regulatory elements recognized by them.

Indexed as

Gene Regulatory NetworksTranscriptomeChlamydomonas reinhardtiiCluster AnalysisDNA, AlgalMultigene FamilyRegulatory Sequences, Nucleic AcidSequence Analysis, RNASoftwareTranscription FactorsDNA, AlgalTranscription FactorsChlamydomonas reinhardtiigene co-expression networksgreen algaelight-regulated transcription factors and transcriptional regulatorsmolecular systems biologyRNA-seqtranscriptomics

Identifiers

PMID26968660
PMCPMC4788957
OpenAlexW2294098372

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.